We derive a signal processing framework, called space signal processing, that parallels time signal processing. As such, it comes in four versions (continuous/discrete, infinite/fi...
Markov jump processes and continuous time Bayesian networks are important classes of continuous time dynamical systems. In this paper, we tackle the problem of inferring unobserve...
Background: Molecular database search tools need statistical models to assess the significance for the resulting hits. In the classical approach one asks the question how probable...
Stefan Wolfsheimer, Inke Herms, Sven Rahmann, Alex...
We present a probabilistic method for audio-visual (AV) speaker tracking, using an uncalibrated wide-angle camera and a microphone array. The algorithm fuses 2-D object shape and ...
Daniel Gatica-Perez, Guillaume Lathoud, Iain McCow...
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...